Modeling Bounded Rationality in Capacity Allocation Games with the Quantal Response Equilibrium

25 Pages Posted: 23 May 2012

See all articles by Yefen Chen

Yefen Chen

Beihang University - School of Economics and Management

Xuanming Su

University of Pennsylvania - Operations & Information Management Department

Xiaobo Zhao

Tsinghua University - Department of Industrial Engineering

Date Written: December 15, 2011

Abstract

We consider a supply chain with a single supplier and two retailers. The retailers choose their orders strategically and if their orders exceed the supplier's capacity, quantities are allocated proportionally to the orders. We experimentally study the capacity allocation game using subjects motivated by financial incentives. We find that the Nash Equilibrium, which assumes that players are perfectly rational, substantially exaggerates retailers' tendency to strategically order more than they need. We propose a model of bounded rationality based on the Quantal Response Equilibrium, in which players are not perfect optimizers and they face uncertainty in their opponents' actions. We structurally estimate model parameters using the maximum likelihood method. Our results confirm that retailers exhibit bounded rationality, become more rational through repeated game play, but may not converge to perfect rationality as assumed by the Nash equilibrium. Finally, we consider several alternative behavioral theories and show that they do not explain our experimental data as well as our bounded rationality model.

Keywords: bounded rationality, capacity allocation, supply chain, quantal response equilibrium, Nash equilibrium

Suggested Citation

Chen, Yefen and Su, Xuanming and Zhao, Xiaobo, Modeling Bounded Rationality in Capacity Allocation Games with the Quantal Response Equilibrium (December 15, 2011). Available at SSRN: https://ssrn.com/abstract=2064854 or http://dx.doi.org/10.2139/ssrn.2064854

Yefen Chen

Beihang University - School of Economics and Management ( email )

37 Xue Yuan Road
Beijing 100083
China

Xuanming Su (Contact Author)

University of Pennsylvania - Operations & Information Management Department ( email )

Philadelphia, PA 19104
United States

Xiaobo Zhao

Tsinghua University - Department of Industrial Engineering ( email )

Beijing
China

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